init

APDrawingGAN2/preprocess/get_partmask.py

@@ -7,8 +7,6 @@ from shapely.geometry import Point
 from shapely.geometry import Polygon
 import sys
 
-detector = dlib.get_frontal_face_detector()
-predictor = dlib.shape_predictor('../checkpoints/shape_predictor_68_face_landmarks.dat')
 
 def getfeats(featpath):
 	trans_points = np.empty([68,2],dtype=np.int64) 
@@ -53,7 +51,7 @@ def shape_to_np(shape, dtype="int"):
 	# return the list of (x, y)-coordinates
 	return coords
 
-def get_68lm(imgfile,savepath):
+def get_68lm(imgfile,savepath, detector, predictor):
 	image = cv2.imread(imgfile)
 	rgbImg = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 	rects = detector(rgbImg, 1)

app.py

@@ -110,22 +110,6 @@ def compress_UUID():
     safe_code = safe_code.replace('-', '')
     return safe_code
 
-
-
-def get_68lm(imgfile, savepath, detector, predictor):
-    image = cv2.imread(imgfile)
-    rgbImg = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-    rects = detector(rgbImg, 1)
-    for (i, rect) in enumerate(rects):
-        landmarks = predictor(rgbImg, rect)
-        landmarks = shape_to_np(landmarks)
-        f = open(savepath, 'w')
-        for i in range(len(landmarks)):
-            lm = landmarks[i]
-            print(lm[0], lm[1], file=f)
-        f.close()
-
-
 def run(
         image,
         model,
@@ -152,7 +136,7 @@ def run(
     imgfile = os.path.join(opt.dataroot, fullname)
     lmfile = os.path.join(opt.lm_dir, name+'.txt')
     # 预处理数据
-    get_68lm(imgfile, lmfile, detector, predictor)
+    get_partmask.get_68lm(imgfile, lmfile, detector, predictor)
 
     imgs = []
     for part in ['eyel', 'eyer', 'nose', 'mouth']: